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🎨 Customization Guide

The Document-to-Podcast Blueprint is designed to be flexible and adaptable to your specific needs. This guide outlines the key parameters you can customize and explains how to make these changes depending on whether you’re running the application via app.py or the CLI pipeline.

🧠 Supported models

There are 2 different parameters to customize the models being used:

text_to_text_model

The language model used to generate the podcast script.

Any model that can be loaded by LLama.from_pretrained can be used here.

Format is expected to be {org}/{repo}/{filename}. For example: Qwen/Qwen2.5-1.5B-Instruct-GGUF/qwen2.5-1.5b-instruct-q8_0.gguf.

text_to_speech_model

The model used to generate the audio from the podcast script.

You can use any of the models listed in TTS_LOADERS out of the box. We currently support OuteTTS.

If you want to use a different model, you can integrate it by implementing the _load and _text_to_speech functions and registering them in TTS_LOADERS and TTS_INFERENCE. You can check this repo where different text-to-speech models are integrated.

🖋️ Other Customizable Parameters

  • input_file: The input file specifies the document to be processed. Supports the following formats: pdf, html, txt, docx, md.

  • text_to_text_prompt: Defines the tone, structure, and instructions for generating the podcast script. This prompt is crucial for tailoring the conversation style to your project.

  • speakers: Defines the podcast participants, including their names, roles, descriptions, and voice profiles. Customize this to create engaging personas and voices for your podcast.

⌨️ Customizing When Running via the CLI

If you’re running the pipeline from the command line, you can customize the parameters by modifying the example_data/config.yaml file.

Running in the CLI: 

document-to-podcast --from_config example_data/config.yaml

Steps to Customize

  1. Open the config.yaml file.
  2. Locate the parameter you want to adjust.
  3. Update the value and save the file.

Example: Changing the Text-to-Text Model

In config.yaml, modify the text_to_text_model entry:

text_to_text_model: "Qwen/Qwen2.5-1.5B-Instruct-GGUF/qwen2.5-1.5b-instruct-q8_0.gguf"

🖥️ Customizing When Running via app.py

If you’re running the application using app.py, you can customize these parameters in the src/config.py file. This centralized configuration file simplifies the customization process.

Running app.py: 

python -m streamlit run demo/app.py

Steps to Customize

  1. Open the config.py file.
  2. Locate the relevant parameter you want to change (e.g., text_to_text_model, speakers).
  3. Update the value according to your needs.

Example: Updating the Prompt

In config.py, modify the text_to_text_prompt parameter:

DEFAULT_PROMPT = """
You are a podcast scriptwriter generating engaging and humorous conversations in JSON format.
The script features the following speakers:
{SPEAKERS}
Instructions:
- Use a casual and fun tone.
- Include jokes and lighthearted banter.
- Format output as a JSON conversation.
  {
    "Speaker 1": "Well we a have a hilarious podcast in store for you today...",
    "Speaker 2": "I can't wait, I had the weirdest week - let me tell you all about it...",
"""

✏️ Customization Examples

Looking for inspiration? Check out these examples of how others have customized the Document-to-Podcast Blueprint for their unique needs:

  • Radio Drama Generator: A creative adaptation that generates radio dramas by customizing ng the Blueprint parameters.
  • Readme-to-Podcast: This project transforms GitHub README files into podcast-style audio, showcasing the Blueprint’s ability to handle diverse text inputs.
  • Multilingual Podcast: A repo that showcases how to use this package in other languages, like Hindi, Polish, Korean and many more.

🤝 Contributing to the Blueprint

Want to help improve or extend this Blueprint? Check out the Future Features & Contributions Guide to see how you can contribute your ideas, code, or feedback to make this Blueprint even better!